| Incremental on-line learning: A review and comparison of state of the art algorithms V Losing, B Hammer, H Wersing Neurocomputing 275, 1261-1274, 2018 | 391 | 2018 |
| KNN Classifier with Self Adjusting Memory for Heterogeneous Concept Drift V Losing, B Hammer, H Wersing 2016 IEEE 16th International Conference on Data Mining (ICDM), 291--300, 2016 | 274 | 2016 |
| Interactive online learning for obstacle classification on a mobile robot V Losing, B Hammer, H Wersing 2015 international joint conference on neural networks (ijcnn), 1-8, 2015 | 64 | 2015 |
| Tackling heterogeneous concept drift with the Self-Adjusting Memory (SAM) V Losing, B Hammer, H Wersing Knowledge and Information Systems 54, 171-201, 2018 | 53 | 2018 |
| Self-adjusting memory: How to deal with diverse drift types V Losing, B Hammer, H Wersing International Joint Conference on Artificial Intelligence, 2017 | 35 | 2017 |
| Choosing the Best Algorithm for an Incremental On-line Learning Task V Losing, B Hammer, H Wersing European Symposium on Artificial Neural Networks (ESANN), 369-374, 2016 | 33 | 2016 |
| Guiding visual search tasks using gaze-contingent auditory feedback V Losing, L Rottkamp, M Zeunert, T Pfeiffer Proceedings of the 2014 ACM International Joint Conference on Pervasive and …, 2014 | 23 | 2014 |
| A multi-modal gait database of natural everyday-walk in an urban environment V Losing, M Hasenjäger Scientific data 9 (1), 473, 2022 | 17 | 2022 |
| Personalized maneuver prediction at intersections V Losing, B Hammer, H Wersing 2017 ieee 20th international conference on intelligent transportation …, 2017 | 15 | 2017 |
| Machine learning for human movement understanding T Yoshikawa, V Losing, E Demircan Advanced Robotics 34 (13), 828-844, 2020 | 14 | 2020 |
| Extraction of common-sense relations from procedural task instructions using BERT V Losing, L Fischer, J Deigmöller Proceedings of the 11th Global Wordnet Conference, 81-90, 2021 | 11 | 2021 |
| Enhancing very fast decision trees with local split-time predictions V Losing, H Wersing, B Hammer 2018 IEEE international conference on data mining (ICDM), 287-296, 2018 | 11 | 2018 |
| Learning fast and slow: A unified batch/stream framework J Montiel, A Bifet, V Losing, J Read, T Abdessalem 2018 IEEE International Conference on Big Data (Big Data), 1065-1072, 2018 | 10 | 2018 |
| Randomizing the self-adjusting memory for enhanced handling of concept drift V Losing, B Hammer, H Wersing, A Bifet 2020 International Joint Conference on Neural Networks (IJCNN), 1-8, 2020 | 9 | 2020 |
| Personalized online learning of whole-body motion classes using multiple inertial measurement units V Losing, T Yoshikawa, M Hasenjaeger, B Hammer, H Wersing 2019 International Conference on Robotics and Automation (ICRA), 9530-9536, 2019 | 8 | 2019 |
| Situational Question Answering using Memory Nets. J Deigmoeller, P Smirnov, V Losing, C Wang, J Takeuchi, J Eggert KDIR, 169-176, 2022 | 6 | 2022 |
| Extraction of common physical properties of everyday objects from structured sources V Losing, J Eggert Proceedings of the 2022 6th International Conference on Natural Language …, 2022 | 2 | 2022 |
| Dedicated Memory Models for Continual Learning in the Presence of Concept Drift V Losing, B Hammer, H Wersing Continual Learning Workshop of the Thirtieth Annual Conference on Neural …, 2016 | 2 | 2016 |
| Personalized Online Learning with Pseudo-Ground Truth V Losing, M Hasenjäger, T Yoshikawa International Conference on Intelligent Robots and Systems, 2020 | 1 | 2020 |
| Memory Models for Incremental Learning Architectures V Losing Bielefeld University, 2019 | | 2019 |
